{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Dropbox\Alecia\Stability of Political Attitudes\Replication Prep\GSS\data\recode\log_recode.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}10 Dec 2025, 19:20:36
{txt}
{com}. 
. /*Code for 2006 Panel*/
. use "original_dataset/GSS_panel06w123_R6a.dta"
{txt}
{com}. 
. keep dateintv_*   natarms_* natenvir_* natfare_* natcrimy_* natrace_* natsci_* partyid_* polviews_* letin1a_* race_* income_* sex_*  age_* degree_*
{txt}
{com}. 
. generate panel_id =  "100"+ string(_n)
{txt}
{com}. destring panel_id, replace
{txt}panel_id: all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}. 
. generate panel = 1
{txt}
{com}. 
. rename *_1 *_2006
{res}{txt}
{com}. rename *_2 *_2008
{res}{txt}
{com}. rename *_3 *_2010
{res}{txt}
{com}. 
. 
. 
. 
. reshape long age_ dateintv_ degree_ natarms_ natcrimy_ natenvir_ natfare_ natrace_ natsci_ partyid_ polviews_ race_ income_ sex_ letin1a_ , i(panel_id) j(year)
{txt}(j = 2006 2008 2010)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}       2,000   {txt}->   {res}6,000       
{txt}Number of variables        {res}          47   {txt}->   {res}18          
{txt}j variable (3 values)                     ->   {res}year
{txt}xij variables:
             {res}age_2006 age_2008 age_2010   {txt}->   {res}age_
dateintv_2006 dateintv_2008 dateintv_2010 {txt}->   {res}dateintv_
    degree_2006 degree_2008 degree_2010   {txt}->   {res}degree_
 natarms_2006 natarms_2008 natarms_2010   {txt}->   {res}natarms_
natcrimy_2006 natcrimy_2008 natcrimy_2010 {txt}->   {res}natcrimy_
natenvir_2006 natenvir_2008 natenvir_2010 {txt}->   {res}natenvir_
 natfare_2006 natfare_2008 natfare_2010   {txt}->   {res}natfare_
 natrace_2006 natrace_2008 natrace_2010   {txt}->   {res}natrace_
    natsci_2006 natsci_2008 natsci_2010   {txt}->   {res}natsci_
 partyid_2006 partyid_2008 partyid_2010   {txt}->   {res}partyid_
polviews_2006 polviews_2008 polviews_2010 {txt}->   {res}polviews_
          race_2006 race_2008 race_2010   {txt}->   {res}race_
    income_2006 income_2008 income_2010   {txt}->   {res}income_
             sex_2006 sex_2008 sex_2010   {txt}->   {res}sex_
 letin1a_2006 letin1a_2008 letin1a_2010   {txt}->   {res}letin1a_
{txt}{hline 77}

{com}. rename *_ *
{res}{txt}
{com}. 
. save "subset_panel/GSS_2006Panel.dta", replace
{txt}{p 0 4 2}
(file {bf}
subset_panel/GSS_2006Panel.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
subset_panel/GSS_2006Panel.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. 
. /*Code for 2008 Panel*/
. 
. use "original_dataset/GSS_panel08w123_R6.dta"
{txt}( )

{com}. 
. 
. keep dateintv_*   natarms_* natenvir_* natfare_* natcrimy_* natrace_* natsci_* partyid_* polviews_* letin1a_* race_* income_* sex_*  age_* degree_*
{txt}
{com}. 
. generate panel_id =  "200"+ string(_n)
{txt}
{com}. destring panel_id, replace
{txt}panel_id: all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}. 
. generate panel = 2
{txt}
{com}. 
. rename *_1 *_2008
{res}{txt}
{com}. rename *_2 *_2010
{res}{txt}
{com}. rename *_3 *_2012
{res}{txt}
{com}. 
. 
. reshape long age_ dateintv_ degree_ natarms_ natcrimy_ natenvir_ natfare_ natrace_ natsci_ partyid_ polviews_ race_ income_ sex_ letin1a_ , i(panel_id) j(year)
{txt}(j = 2008 2010 2012)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}       2,023   {txt}->   {res}6,069       
{txt}Number of variables        {res}          47   {txt}->   {res}18          
{txt}j variable (3 values)                     ->   {res}year
{txt}xij variables:
             {res}age_2008 age_2010 age_2012   {txt}->   {res}age_
dateintv_2008 dateintv_2010 dateintv_2012 {txt}->   {res}dateintv_
    degree_2008 degree_2010 degree_2012   {txt}->   {res}degree_
 natarms_2008 natarms_2010 natarms_2012   {txt}->   {res}natarms_
natcrimy_2008 natcrimy_2010 natcrimy_2012 {txt}->   {res}natcrimy_
natenvir_2008 natenvir_2010 natenvir_2012 {txt}->   {res}natenvir_
 natfare_2008 natfare_2010 natfare_2012   {txt}->   {res}natfare_
 natrace_2008 natrace_2010 natrace_2012   {txt}->   {res}natrace_
    natsci_2008 natsci_2010 natsci_2012   {txt}->   {res}natsci_
 partyid_2008 partyid_2010 partyid_2012   {txt}->   {res}partyid_
polviews_2008 polviews_2010 polviews_2012 {txt}->   {res}polviews_
          race_2008 race_2010 race_2012   {txt}->   {res}race_
    income_2008 income_2010 income_2012   {txt}->   {res}income_
             sex_2008 sex_2010 sex_2012   {txt}->   {res}sex_
 letin1a_2008 letin1a_2010 letin1a_2012   {txt}->   {res}letin1a_
{txt}{hline 77}

{com}. rename *_ *
{res}{txt}
{com}. 
. save "subset_panel/GSS_2008Panel.dta", replace
{txt}{p 0 4 2}
(file {bf}
subset_panel/GSS_2008Panel.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
subset_panel/GSS_2008Panel.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. 
. 
. /*Code for 2010 Panel*/
. 
. use "original_dataset/GSS_panel2010w123_R6.dta"
{txt}( )

{com}. 
. 
. keep dateintv_*   natarms_* natenvir_* natfare_* natcrimy_* natrace_* natsci_* partyid_* polviews_* letin1a_* race_* income_* sex_*  age_* degree_*
{txt}
{com}. 
. generate panel_id =  "300"+ string(_n)
{txt}
{com}. destring panel_id, replace
{txt}panel_id: all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}. 
. generate panel = 3
{txt}
{com}. 
. rename *_1 *_2010
{res}{txt}
{com}. rename *_2 *_2012
{res}{txt}
{com}. rename *_3 *_2014
{res}{txt}
{com}. 
. 
. reshape long age_ dateintv_ degree_  natarms_ natcrimy_ natenvir_ natfare_ natrace_ natsci_ partyid_ polviews_ race_ income_ sex_ letin1a_ , i(panel_id) j(year)
{txt}(j = 2010 2012 2014)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}       2,044   {txt}->   {res}6,132       
{txt}Number of variables        {res}          47   {txt}->   {res}18          
{txt}j variable (3 values)                     ->   {res}year
{txt}xij variables:
             {res}age_2010 age_2012 age_2014   {txt}->   {res}age_
dateintv_2010 dateintv_2012 dateintv_2014 {txt}->   {res}dateintv_
    degree_2010 degree_2012 degree_2014   {txt}->   {res}degree_
 natarms_2010 natarms_2012 natarms_2014   {txt}->   {res}natarms_
natcrimy_2010 natcrimy_2012 natcrimy_2014 {txt}->   {res}natcrimy_
natenvir_2010 natenvir_2012 natenvir_2014 {txt}->   {res}natenvir_
 natfare_2010 natfare_2012 natfare_2014   {txt}->   {res}natfare_
 natrace_2010 natrace_2012 natrace_2014   {txt}->   {res}natrace_
    natsci_2010 natsci_2012 natsci_2014   {txt}->   {res}natsci_
 partyid_2010 partyid_2012 partyid_2014   {txt}->   {res}partyid_
polviews_2010 polviews_2012 polviews_2014 {txt}->   {res}polviews_
          race_2010 race_2012 race_2014   {txt}->   {res}race_
    income_2010 income_2012 income_2014   {txt}->   {res}income_
             sex_2010 sex_2012 sex_2014   {txt}->   {res}sex_
 letin1a_2010 letin1a_2012 letin1a_2014   {txt}->   {res}letin1a_
{txt}{hline 77}

{com}. rename *_ *
{res}{txt}
{com}. 
. 
. save "subset_panel/GSS_2010Panel.dta", replace
{txt}{p 0 4 2}
(file {bf}
subset_panel/GSS_2010Panel.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
subset_panel/GSS_2010Panel.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. 
. 
. /*Code for 2016-2020 Panel*/
. 
. use "original_dataset/gss2020panel_r1a.dta"
{txt}
{com}. 
. 
. keep dateintv_*   natarms_* natenvir_* natfare_* natcrimy_* natrace_* natsci_* partyid_* polviews_* letin1a_* race_* income_* sex_*  age_* degree_*
{txt}
{com}. 
. generate panel_id =  "400"+ string(_n)
{txt}
{com}. destring panel_id, replace
{txt}panel_id: all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}. 
. generate panel = 4
{txt}
{com}. 
. rename *_1a *_2016
{res}{txt}
{com}. rename *_1b *_2018
{res}{txt}
{com}. rename *_2 *_2020
{res}{txt}
{com}. 
. reshape long age_ dateintv_ degree_ natarms_ natcrimy_ natenvir_ natfare_ natrace_ natsci_ partyid_ polviews_ race_ income_ sex_ letin1a_ , i(panel_id) j(year)
{txt}(j = 2016 2018 2020)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}       5,215   {txt}->   {res}15,645      
{txt}Number of variables        {res}          47   {txt}->   {res}18          
{txt}j variable (3 values)                     ->   {res}year
{txt}xij variables:
             {res}age_2016 age_2018 age_2020   {txt}->   {res}age_
dateintv_2016 dateintv_2018 dateintv_2020 {txt}->   {res}dateintv_
    degree_2016 degree_2018 degree_2020   {txt}->   {res}degree_
 natarms_2016 natarms_2018 natarms_2020   {txt}->   {res}natarms_
natcrimy_2016 natcrimy_2018 natcrimy_2020 {txt}->   {res}natcrimy_
natenvir_2016 natenvir_2018 natenvir_2020 {txt}->   {res}natenvir_
 natfare_2016 natfare_2018 natfare_2020   {txt}->   {res}natfare_
 natrace_2016 natrace_2018 natrace_2020   {txt}->   {res}natrace_
    natsci_2016 natsci_2018 natsci_2020   {txt}->   {res}natsci_
 partyid_2016 partyid_2018 partyid_2020   {txt}->   {res}partyid_
polviews_2016 polviews_2018 polviews_2020 {txt}->   {res}polviews_
          race_2016 race_2018 race_2020   {txt}->   {res}race_
    income_2016 income_2018 income_2020   {txt}->   {res}income_
             sex_2016 sex_2018 sex_2020   {txt}->   {res}sex_
 letin1a_2016 letin1a_2018 letin1a_2020   {txt}->   {res}letin1a_
{txt}{hline 77}

{com}. rename *_ *
{res}{txt}
{com}. 
. save "subset_panel/GSS_2016_2020Panel.dta", replace
{txt}{p 0 4 2}
(file {bf}
subset_panel/GSS_2016_2020Panel.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
subset_panel/GSS_2016_2020Panel.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. 
. /*Appending datasets and removing observations with all retained variables missing*/
. 
. append using "subset_panel/GSS_2006Panel.dta" "subset_panel/GSS_2008Panel.dta" "subset_panel/GSS_2010Panel.dta" "subset_panel/GSS_2016_2020Panel.dta"
{txt}(label {bf:{txt}SEX_3} already defined)
(label {bf:{txt}DEGREE_3} already defined)
(label {bf:{txt}AGE_3} already defined)
(label {bf:{txt}LABB} already defined)
(label {bf:{txt}SEX_3} already defined)
(label {bf:{txt}RACE_3} already defined)
(label {bf:{txt}NATSCI_3} already defined)
(label {bf:{txt}INCOME_3} already defined)
(label {bf:{txt}DEGREE_3} already defined)
(label {bf:{txt}AGE_3} already defined)

{com}. 
. 
. drop if inlist(age, .i, .y, .d, .n, .s, .a)  & inlist(dateintv, .i, .y, .d, .n, .s, .a) & inlist(degree, .i, .y, .d, .n, .s, .a) & inlist(natarms, .i, .y, .d, .n, .s, .a)  & inlist(natcrimy, .i, .y, .d, .n, .s, .a) & inlist(natenvir, .i, .y, .d, .n, .s, .a) & inlist(natfare, .i, .y, .d, .n, .s, .a) & inlist(natrace, .i, .y, .d, .n, .s, .a) & inlist(natsci, .i, .y, .d, .n, .s, .a)  & inlist(partyid, .i, .y, .d, .n, .s, .a)  & inlist(polviews, .i, .y, .d, .n, .s, .a) & inlist(race, .i, .y, .d, .n, .s, .a) & inlist(income, .i, .y, .d, .n, .s, .a) & inlist(sex, .i, .y, .d, .n, .s, .a)   & inlist(letin1a, .i, .y, .d, .n, .s, .a) 
{txt}(12,198 observations deleted)

{com}. 
. 
. save "GSS_2006_2020AppendedPanels.dta", replace
{txt}{p 0 4 2}
(file {bf}
GSS_2006_2020AppendedPanels.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
GSS_2006_2020AppendedPanels.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. 
. 
. /****** Section 2: Recoded stacked panels dataset as outlined in the provided codebook******/
. 
. use "GSS_2006_2020AppendedPanels.dta"
{txt}
{com}. 
. codebook *

{txt}{hline}
{res}panel_id{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}long{txt})

{col 18}Range: [{res}1001{txt},{res}4005215{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}11,282{col 51}{txt}Missing .: {res}0{txt}/{res}21,648

{txt}{col 19}Mean: {res}{ralign 7:1.8e+06}
{txt}{col 14}Std. dev.: {res}{ralign 7:1.6e+06}

{txt}{col 12}Percentiles: {col 25}{ralign 7:10%}{ralign 10:25%}{ralign 10:50%}{ralign 10:75%}{ralign 10:90%}
{res}{col 25}{ralign 7:100668}{ralign 10:  300222}{ralign 10: 1.0e+06}{ralign 10: 4.0e+06}{ralign 10: 4.0e+06}

{txt}{hline}
{res}year{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}int{txt})

{col 18}Range: [{res}2006{txt},{res}2020{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}8{col 51}{txt}Missing .: {res}0{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.  Value
{col 20}{res}     2,000{col 32}2006
{col 20}     3,559{col 32}2008
{col 20}     4,901{col 32}2010
{col 20}     2,846{col 32}2012
{col 20}     1,304{col 32}2014
{col 20}     2,867{col 32}2016
{col 20}     2,348{col 32}2018
{col 20}     1,823{col 32}2020

{txt}{hline}
{res}age{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:AGE_3}, but {res:71} nonmissing values are not labeled

{col 18}Range: [{res}18{txt},{res}89{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}72{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}162{txt}/{res}21,648

{txt}{ralign 23: Examples:}{col 25}{res}32{col 31}{txt}
{ralign 23: }{col 25}{res}44{col 31}{txt}
{ralign 23: }{col 25}{res}54{col 31}{txt}
{ralign 23: }{col 25}{res}66{col 31}{txt}

{txt}{hline}
{res}dateintv{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}int{txt})
{ralign 22:Label}: {res:LABAP}, but {res:258} nonmissing values are not labeled

{col 18}Range: [{res}307{txt},{res}1119{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}258{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}1{txt}/{res}21,648

{txt}{ralign 23: Examples:}{col 25}{res}416{col 31}{txt}
{ralign 23: }{col 25}{res}507{col 31}{txt}
{ralign 23: }{col 25}{res}606{col 31}{txt}
{ralign 23: }{col 25}{res}722{col 31}{txt}

{txt}{hline}
{res}degree{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:DEGREE_3}

{col 18}Range: [{res}0{txt},{res}4{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}5{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}3{col 50}{txt}Missing .*: {res}19{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     2,584{col 32}       0{col 42}{txt}lt high school
{col 20}{res}    10,720{col 32}       1{col 42}{txt}high school
{col 20}{res}     1,721{col 32}       2{col 42}{txt}junior college
{col 20}{res}     4,190{col 32}       3{col 42}{txt}bachelor
{col 20}{res}     2,414{col 32}       4{col 42}{txt}graduate
{col 20}{res}         2{col 32}      .a{col 42}
{col 20}         1{col 32}      .d{col 42}
{col 20}        16{col 32}      .n{col 42}

{txt}{hline}
{res}income{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABER}

{col 18}Range: [{res}1{txt},{res}13{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}13{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}2,445{txt}/{res}21,648

{txt}{ralign 23: Examples:}{col 25}{res}11{col 31}{txt}$20000 - 24999
{ralign 23: }{col 25}{res}12{col 31}{txt}$25000 or more
{ralign 23: }{col 25}{res}12{col 31}{txt}$25000 or more
{ralign 23: }{col 25}{res}12{col 31}{txt}$25000 or more

{txt}{hline}
{res}natarms{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,177{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     3,002{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,899{col 32}       2{col 42}{txt}about right
{col 20}{res}     3,570{col 32}       3{col 42}{txt}too much
{col 20}{res}       268{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        10{col 32}      .n{col 42}{txt}NA
{col 20}{res}         4{col 32}      .s{col 42}

{txt}{hline}
{res}natcrimy{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}10,963{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     5,566{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,909{col 32}       2{col 42}{txt}about right
{col 20}{res}     1,210{col 32}       3{col 42}{txt}too much
{col 20}{res}       191{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,754{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        12{col 32}      .n{col 42}{txt}NA
{col 20}{res}         6{col 32}      .s{col 42}

{txt}{hline}
{res}natenvir{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,137{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     6,662{col 32}       1{col 42}{txt}too little
{col 20}{res}     2,959{col 32}       2{col 42}{txt}about right
{col 20}{res}       890{col 32}       3{col 42}{txt}too much
{col 20}{res}       235{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}         5{col 32}      .n{col 42}{txt}NA
{col 20}{res}         2{col 32}      .s{col 42}

{txt}{hline}
{res}natfare{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,248{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     2,465{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,752{col 32}       2{col 42}{txt}about right
{col 20}{res}     4,183{col 32}       3{col 42}{txt}too much
{col 20}{res}       333{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        16{col 32}      .n{col 42}{txt}NA
{col 20}{res}         4{col 32}      .s{col 42}

{txt}{hline}
{res}natrace{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,887{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     4,072{col 32}       1{col 42}{txt}too little
{col 20}{res}     4,365{col 32}       2{col 42}{txt}about right
{col 20}{res}     1,324{col 32}       3{col 42}{txt}too much
{col 20}{res}       882{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}       101{col 32}      .n{col 42}{txt}NA
{col 20}{res}         9{col 32}      .s{col 42}

{txt}{hline}
{res}natsci{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}3{col 50}{txt}Missing .*: {res}1,229{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     8,461{col 32}       1{col 42}{txt}too little
{col 20}{res}     9,647{col 32}       2{col 42}{txt}about right
{col 20}{res}     2,311{col 32}       3{col 42}{txt}too much
{col 20}{res}     1,205{col 32}      .d{col 42}{txt}DK
{col 20}{res}        15{col 32}      .n{col 42}{txt}NA
{col 20}{res}         9{col 32}      .s{col 42}

{txt}{hline}
{res}partyid{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:V2725_A}

{col 18}Range: [{res}0{txt},{res}7{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}8{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}2{col 50}{txt}Missing .*: {res}170{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     3,777{col 32}       0{col 42}{txt}strong democrat
{col 20}{res}     3,588{col 32}       1{col 42}{txt}not str democrat
{col 20}{res}     2,770{col 32}       2{col 42}{txt}ind,near dem
{col 20}{res}     3,658{col 32}       3{col 42}{txt}independent
{col 20}{res}     2,068{col 32}       4{col 42}{txt}ind,near rep
{col 20}{res}     2,816{col 32}       5{col 42}{txt}not str republican
{col 20}{res}     2,303{col 32}       6{col 42}{txt}strong republican
{col 20}{res}       498{col 32}       7{col 42}{txt}other party
{col 20}{res}         3{col 32}      .d{col 42}{txt}DK
{col 20}{res}       167{col 32}      .n{col 42}{txt}NA

{txt}{hline}
{res}polviews{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABIU}

{col 18}Range: [{res}1{txt},{res}7{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}7{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}712{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}       866{col 32}       1{col 42}{txt}extremely liberal
{col 20}{res}     2,672{col 32}       2{col 42}{txt}liberal
{col 20}{res}     2,482{col 32}       3{col 42}{txt}slightly liberal
{col 20}{res}     7,776{col 32}       4{col 42}{txt}moderate
{col 20}{res}     2,934{col 32}       5{col 42}{txt}slghtly conservative
{col 20}{res}     3,336{col 32}       6{col 42}{txt}conservative
{col 20}{res}       870{col 32}       7{col 42}{txt}extrmly conservative
{col 20}{res}       567{col 32}      .d{col 42}{txt}DK
{col 20}{res}         4{col 32}      .i{col 42}{txt}IAP
{col 20}{res}       129{col 32}      .n{col 42}{txt}NA
{col 20}{res}        12{col 32}      .s{col 42}

{txt}{hline}
{res}race{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABJG}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}1,823{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}    15,043{col 32}       1{col 42}{txt}white
{col 20}{res}     2,989{col 32}       2{col 42}{txt}black
{col 20}{res}     1,793{col 32}       3{col 42}{txt}other
{col 20}{res}     1,823{col 32}      .y{col 42}

{txt}{hline}
{res}sex{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:SEX_3}

{col 18}Range: [{res}1{txt},{res}2{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}2{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}10{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     9,481{col 32}       1{col 42}{txt}male
{col 20}{res}    12,157{col 32}       2{col 42}{txt}female
{col 20}{res}        10{col 32}      .n{col 42}

{txt}{hline}
{res}letin1a{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABMU}

{col 18}Range: [{res}1{txt},{res}5{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}5{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}8,872{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}       639{col 32}       1{col 42}{txt}increased a lot
{col 20}{res}     1,358{col 32}       2{col 42}{txt}increased a little
{col 20}{res}     4,907{col 32}       3{col 42}{txt}remain the same as it is
{col 20}{res}     2,965{col 32}       4{col 42}{txt}reduced a little
{col 20}{res}     2,907{col 32}       5{col 42}{txt}reduced a lot
{col 20}{res}       247{col 32}      .d{col 42}{txt}Don't know
{col 20}{res}     8,564{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        49{col 32}      .n{col 42}{txt}No Answer
{col 20}{res}        12{col 32}      .s{col 42}

{txt}{hline}
{res}panel{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}float{txt})

{col 18}Range: [{res}1{txt},{res}4{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}4{col 51}{txt}Missing .: {res}0{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.  Value
{col 20}{res}     4,812{col 32}1
{col 20}     4,899{col 32}2
{col 20}     4,899{col 32}3
{col 20}     7,038{col 32}4
{txt}
{com}. 
. /*Format interview date*/
. generate dayintv = mod(dateintv, 100)
{txt}(1 missing value generated)

{com}. 
. generate monthintv = floor(dateintv /100)
{txt}(1 missing value generated)

{com}. 
. rename year yearintv
{res}{txt}
{com}. 
. generate stata_intvdate = mdy(monthintv, dayintv, yearintv )
{txt}(1 missing value generated)

{com}. 
. label variable stata_intvdate "interview date in days since Jan. 1. 1960"
{txt}
{com}. 
. generate combined_id = _n
{txt}
{com}. 
. 
. /*Reverse coding DVs*/
. 
. 
. codebook natarms 

{txt}{hline}
{res}natarms{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,177{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     3,002{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,899{col 32}       2{col 42}{txt}about right
{col 20}{res}     3,570{col 32}       3{col 42}{txt}too much
{col 20}{res}       268{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        10{col 32}      .n{col 42}{txt}NA
{col 20}{res}         4{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natarms = natarms 
{txt}(11,177 missing values generated)

{com}. replace rec_natarms = 1 if natarms == 3
{txt}(3,570 real changes made)

{com}. replace rec_natarms = 2 if natarms == 2
{txt}(0 real changes made)

{com}. replace rec_natarms = 3 if natarms == 1
{txt}(3,002 real changes made)

{com}. 
. tab rec_natarms natarms, missing 

{txt}rec_natarm {c |}                                   natarms
         s {c |} too littl  about rig   too much         DK        IAP         NA         .s {c |}     Total
{hline 11}{c +}{hline 77}{c +}{hline 10}
         1 {c |}{res}         0          0      3,570          0          0          0          0 {txt}{c |}{res}     3,570 
{txt}         2 {c |}{res}         0      3,899          0          0          0          0          0 {txt}{c |}{res}     3,899 
{txt}         3 {c |}{res}     3,002          0          0          0          0          0          0 {txt}{c |}{res}     3,002 
{txt}        .d {c |}{res}         0          0          0        268          0          0          0 {txt}{c |}{res}       268 
{txt}        .i {c |}{res}         0          0          0          0     10,895          0          0 {txt}{c |}{res}    10,895 
{txt}        .n {c |}{res}         0          0          0          0          0         10          0 {txt}{c |}{res}        10 
{txt}        .s {c |}{res}         0          0          0          0          0          0          4 {txt}{c |}{res}         4 
{txt}{hline 11}{c +}{hline 77}{c +}{hline 10}
     Total {c |}{res}     3,002      3,899      3,570        268     10,895         10          4 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. 
. 
. 
. codebook natcrimy 

{txt}{hline}
{res}natcrimy{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}10,963{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     5,566{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,909{col 32}       2{col 42}{txt}about right
{col 20}{res}     1,210{col 32}       3{col 42}{txt}too much
{col 20}{res}       191{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,754{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        12{col 32}      .n{col 42}{txt}NA
{col 20}{res}         6{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natcrimy = natcrimy 
{txt}(10,963 missing values generated)

{com}. replace rec_natcrimy = 1 if natcrimy == 3
{txt}(1,210 real changes made)

{com}. replace rec_natcrimy = 2 if natcrimy == 2
{txt}(0 real changes made)

{com}. replace rec_natcrimy = 3 if natcrimy == 1
{txt}(5,566 real changes made)

{com}. 
. tab rec_natcrimy natcrimy, missing 

{txt}rec_natcri {c |}                                   natcrimy
        my {c |} too littl  about rig   too much         DK        IAP         NA         .s {c |}     Total
{hline 11}{c +}{hline 77}{c +}{hline 10}
         1 {c |}{res}         0          0      1,210          0          0          0          0 {txt}{c |}{res}     1,210 
{txt}         2 {c |}{res}         0      3,909          0          0          0          0          0 {txt}{c |}{res}     3,909 
{txt}         3 {c |}{res}     5,566          0          0          0          0          0          0 {txt}{c |}{res}     5,566 
{txt}        .d {c |}{res}         0          0          0        191          0          0          0 {txt}{c |}{res}       191 
{txt}        .i {c |}{res}         0          0          0          0     10,754          0          0 {txt}{c |}{res}    10,754 
{txt}        .n {c |}{res}         0          0          0          0          0         12          0 {txt}{c |}{res}        12 
{txt}        .s {c |}{res}         0          0          0          0          0          0          6 {txt}{c |}{res}         6 
{txt}{hline 11}{c +}{hline 77}{c +}{hline 10}
     Total {c |}{res}     5,566      3,909      1,210        191     10,754         12          6 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. 
. codebook natenvir 

{txt}{hline}
{res}natenvir{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,137{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     6,662{col 32}       1{col 42}{txt}too little
{col 20}{res}     2,959{col 32}       2{col 42}{txt}about right
{col 20}{res}       890{col 32}       3{col 42}{txt}too much
{col 20}{res}       235{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}         5{col 32}      .n{col 42}{txt}NA
{col 20}{res}         2{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natenvir = natenvir
{txt}(11,137 missing values generated)

{com}. replace rec_natenvir = 1 if natenvir == 3
{txt}(890 real changes made)

{com}. replace rec_natenvir = 2 if natenvir == 2
{txt}(0 real changes made)

{com}. replace rec_natenvir = 3 if natenvir == 1
{txt}(6,662 real changes made)

{com}. 
. tab rec_natenvir natenvir, missing 

{txt}rec_natenv {c |}                                   natenvir
        ir {c |} too littl  about rig   too much         DK        IAP         NA         .s {c |}     Total
{hline 11}{c +}{hline 77}{c +}{hline 10}
         1 {c |}{res}         0          0        890          0          0          0          0 {txt}{c |}{res}       890 
{txt}         2 {c |}{res}         0      2,959          0          0          0          0          0 {txt}{c |}{res}     2,959 
{txt}         3 {c |}{res}     6,662          0          0          0          0          0          0 {txt}{c |}{res}     6,662 
{txt}        .d {c |}{res}         0          0          0        235          0          0          0 {txt}{c |}{res}       235 
{txt}        .i {c |}{res}         0          0          0          0     10,895          0          0 {txt}{c |}{res}    10,895 
{txt}        .n {c |}{res}         0          0          0          0          0          5          0 {txt}{c |}{res}         5 
{txt}        .s {c |}{res}         0          0          0          0          0          0          2 {txt}{c |}{res}         2 
{txt}{hline 11}{c +}{hline 77}{c +}{hline 10}
     Total {c |}{res}     6,662      2,959        890        235     10,895          5          2 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. codebook natfare 

{txt}{hline}
{res}natfare{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,248{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     2,465{col 32}       1{col 42}{txt}too little
{col 20}{res}     3,752{col 32}       2{col 42}{txt}about right
{col 20}{res}     4,183{col 32}       3{col 42}{txt}too much
{col 20}{res}       333{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        16{col 32}      .n{col 42}{txt}NA
{col 20}{res}         4{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natfare = natfare
{txt}(11,248 missing values generated)

{com}. replace rec_natfare = 1 if natfare == 3
{txt}(4,183 real changes made)

{com}. replace rec_natfare = 2 if natfare == 2
{txt}(0 real changes made)

{com}. replace rec_natfare = 3 if natfare == 1
{txt}(2,465 real changes made)

{com}. 
. tab rec_natfare natfare, missing 

{txt}rec_natfar {c |}                                   natfare
         e {c |} too littl  about rig   too much         DK        IAP         NA         .s {c |}     Total
{hline 11}{c +}{hline 77}{c +}{hline 10}
         1 {c |}{res}         0          0      4,183          0          0          0          0 {txt}{c |}{res}     4,183 
{txt}         2 {c |}{res}         0      3,752          0          0          0          0          0 {txt}{c |}{res}     3,752 
{txt}         3 {c |}{res}     2,465          0          0          0          0          0          0 {txt}{c |}{res}     2,465 
{txt}        .d {c |}{res}         0          0          0        333          0          0          0 {txt}{c |}{res}       333 
{txt}        .i {c |}{res}         0          0          0          0     10,895          0          0 {txt}{c |}{res}    10,895 
{txt}        .n {c |}{res}         0          0          0          0          0         16          0 {txt}{c |}{res}        16 
{txt}        .s {c |}{res}         0          0          0          0          0          0          4 {txt}{c |}{res}         4 
{txt}{hline 11}{c +}{hline 77}{c +}{hline 10}
     Total {c |}{res}     2,465      3,752      4,183        333     10,895         16          4 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. codebook natrace 

{txt}{hline}
{res}natrace{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}11,887{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     4,072{col 32}       1{col 42}{txt}too little
{col 20}{res}     4,365{col 32}       2{col 42}{txt}about right
{col 20}{res}     1,324{col 32}       3{col 42}{txt}too much
{col 20}{res}       882{col 32}      .d{col 42}{txt}DK
{col 20}{res}    10,895{col 32}      .i{col 42}{txt}IAP
{col 20}{res}       101{col 32}      .n{col 42}{txt}NA
{col 20}{res}         9{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natrace = natrace
{txt}(11,887 missing values generated)

{com}. replace rec_natrace = 1 if natrace == 3
{txt}(1,324 real changes made)

{com}. replace rec_natrace = 2 if natrace == 2
{txt}(0 real changes made)

{com}. replace rec_natrace = 3 if natrace == 1
{txt}(4,072 real changes made)

{com}. 
. tab rec_natrace natrace, missing 

{txt}rec_natrac {c |}                                   natrace
         e {c |} too littl  about rig   too much         DK        IAP         NA         .s {c |}     Total
{hline 11}{c +}{hline 77}{c +}{hline 10}
         1 {c |}{res}         0          0      1,324          0          0          0          0 {txt}{c |}{res}     1,324 
{txt}         2 {c |}{res}         0      4,365          0          0          0          0          0 {txt}{c |}{res}     4,365 
{txt}         3 {c |}{res}     4,072          0          0          0          0          0          0 {txt}{c |}{res}     4,072 
{txt}        .d {c |}{res}         0          0          0        882          0          0          0 {txt}{c |}{res}       882 
{txt}        .i {c |}{res}         0          0          0          0     10,895          0          0 {txt}{c |}{res}    10,895 
{txt}        .n {c |}{res}         0          0          0          0          0        101          0 {txt}{c |}{res}       101 
{txt}        .s {c |}{res}         0          0          0          0          0          0          9 {txt}{c |}{res}         9 
{txt}{hline 11}{c +}{hline 77}{c +}{hline 10}
     Total {c |}{res}     4,072      4,365      1,324        882     10,895        101          9 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. codebook natsci 

{txt}{hline}
{res}natsci{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABHA}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}3{col 50}{txt}Missing .*: {res}1,229{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     8,461{col 32}       1{col 42}{txt}too little
{col 20}{res}     9,647{col 32}       2{col 42}{txt}about right
{col 20}{res}     2,311{col 32}       3{col 42}{txt}too much
{col 20}{res}     1,205{col 32}      .d{col 42}{txt}DK
{col 20}{res}        15{col 32}      .n{col 42}{txt}NA
{col 20}{res}         9{col 32}      .s{col 42}
{txt}
{com}. 
. generate rec_natsci = natsci
{txt}(1,229 missing values generated)

{com}. replace rec_natsci = 1 if natsci == 3
{txt}(2,311 real changes made)

{com}. replace rec_natsci = 2 if natsci == 2
{txt}(0 real changes made)

{com}. replace rec_natsci = 3 if natsci == 1
{txt}(8,461 real changes made)

{com}. 
. tab rec_natsci natsci, missing 

           {txt}{c |}                              natsci
rec_natsci {c |} too littl  about rig   too much         DK         NA         .s {c |}     Total
{hline 11}{c +}{hline 66}{c +}{hline 10}
         1 {c |}{res}         0          0      2,311          0          0          0 {txt}{c |}{res}     2,311 
{txt}         2 {c |}{res}         0      9,647          0          0          0          0 {txt}{c |}{res}     9,647 
{txt}         3 {c |}{res}     8,461          0          0          0          0          0 {txt}{c |}{res}     8,461 
{txt}        .d {c |}{res}         0          0          0      1,205          0          0 {txt}{c |}{res}     1,205 
{txt}        .n {c |}{res}         0          0          0          0         15          0 {txt}{c |}{res}        15 
{txt}        .s {c |}{res}         0          0          0          0          0          9 {txt}{c |}{res}         9 
{txt}{hline 11}{c +}{hline 66}{c +}{hline 10}
     Total {c |}{res}     8,461      9,647      2,311      1,205         15          9 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. codebook letin1a

{txt}{hline}
{res}letin1a{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABMU}

{col 18}Range: [{res}1{txt},{res}5{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}5{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}8,872{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}       639{col 32}       1{col 42}{txt}increased a lot
{col 20}{res}     1,358{col 32}       2{col 42}{txt}increased a little
{col 20}{res}     4,907{col 32}       3{col 42}{txt}remain the same as it is
{col 20}{res}     2,965{col 32}       4{col 42}{txt}reduced a little
{col 20}{res}     2,907{col 32}       5{col 42}{txt}reduced a lot
{col 20}{res}       247{col 32}      .d{col 42}{txt}Don't know
{col 20}{res}     8,564{col 32}      .i{col 42}{txt}IAP
{col 20}{res}        49{col 32}      .n{col 42}{txt}No Answer
{col 20}{res}        12{col 32}      .s{col 42}
{txt}
{com}.  
. generate rec_letin1a = letin1a
{txt}(8,872 missing values generated)

{com}. replace rec_letin1a = 1 if letin1a == 5
{txt}(2,907 real changes made)

{com}. replace rec_letin1a = 2 if letin1a == 4
{txt}(2,965 real changes made)

{com}. replace rec_letin1a = 3 if letin1a == 3
{txt}(0 real changes made)

{com}. replace rec_letin1a = 4 if letin1a == 2
{txt}(1,358 real changes made)

{com}. replace rec_letin1a = 5 if letin1a == 1
{txt}(639 real changes made)

{com}. 
. tab rec_letin1a letin1a, missing 

{txt}rec_letin1 {c |}                                              letin1a
         a {c |} increased  increased  remain th  reduced a  reduced a  Don't kno        IAP  No Answer         .s {c |}     Total
{hline 11}{c +}{hline 99}{c +}{hline 10}
         1 {c |}{res}         0          0          0          0      2,907          0          0          0          0 {txt}{c |}{res}     2,907 
{txt}         2 {c |}{res}         0          0          0      2,965          0          0          0          0          0 {txt}{c |}{res}     2,965 
{txt}         3 {c |}{res}         0          0      4,907          0          0          0          0          0          0 {txt}{c |}{res}     4,907 
{txt}         4 {c |}{res}         0      1,358          0          0          0          0          0          0          0 {txt}{c |}{res}     1,358 
{txt}         5 {c |}{res}       639          0          0          0          0          0          0          0          0 {txt}{c |}{res}       639 
{txt}        .d {c |}{res}         0          0          0          0          0        247          0          0          0 {txt}{c |}{res}       247 
{txt}        .i {c |}{res}         0          0          0          0          0          0      8,564          0          0 {txt}{c |}{res}     8,564 
{txt}        .n {c |}{res}         0          0          0          0          0          0          0         49          0 {txt}{c |}{res}        49 
{txt}        .s {c |}{res}         0          0          0          0          0          0          0          0         12 {txt}{c |}{res}        12 
{txt}{hline 11}{c +}{hline 99}{c +}{hline 10}
     Total {c |}{res}       639      1,358      4,907      2,965      2,907        247      8,564         49         12 {txt}{c |}{res}    21,648 
{txt}
{com}. 
. 
. /*Code partyid == other party as partyid = independent*/
. 
. clonevar rec_partyid = partyid
{txt}(170 missing values generated)

{com}. replace rec_partyid = 3 if partyid == 7
{txt}(498 real changes made)

{com}. 
. codebook polviews

{txt}{hline}
{res}polviews{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABIU}

{col 18}Range: [{res}1{txt},{res}7{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}7{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}4{col 50}{txt}Missing .*: {res}712{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}       866{col 32}       1{col 42}{txt}extremely liberal
{col 20}{res}     2,672{col 32}       2{col 42}{txt}liberal
{col 20}{res}     2,482{col 32}       3{col 42}{txt}slightly liberal
{col 20}{res}     7,776{col 32}       4{col 42}{txt}moderate
{col 20}{res}     2,934{col 32}       5{col 42}{txt}slghtly conservative
{col 20}{res}     3,336{col 32}       6{col 42}{txt}conservative
{col 20}{res}       870{col 32}       7{col 42}{txt}extrmly conservative
{col 20}{res}       567{col 32}      .d{col 42}{txt}DK
{col 20}{res}         4{col 32}      .i{col 42}{txt}IAP
{col 20}{res}       129{col 32}      .n{col 42}{txt}NA
{col 20}{res}        12{col 32}      .s{col 42}
{txt}
{com}. 
. 
. /*Recode explanatory variables*/
. 
. //Code family income last fall before taxes
. 
. clonevar rec_income = income
{txt}(2,445 missing values generated)

{com}. replace rec_income = 888 if income == .a
{txt}variable {bf}{res}rec_income{sf}{txt} was {bf}{res}byte{sf}{txt} now {bf}{res}int{sf}
{txt}(1,475 real changes made)

{com}. replace rec_income = 1 if income < 10
{txt}(2,629 real changes made)

{com}. replace rec_income = 2 if income == 10 | income == 11
{txt}(2,334 real changes made)

{com}. replace rec_income = 3 if income == 12
{txt}(13,769 real changes made)

{com}. 
. tab income rec_income 

               {txt}{c |}                 rec_income
        income {c |}  lt $1000  $1000 to   $3000 to     refused {c |}     Total
{hline 15}{c +}{hline 44}{c +}{hline 10}
      lt $1000 {c |}{res}       281          0          0          0 {txt}{c |}{res}       281 
{txt} $1000 to 2999 {c |}{res}       241          0          0          0 {txt}{c |}{res}       241 
{txt} $3000 to 3999 {c |}{res}       153          0          0          0 {txt}{c |}{res}       153 
{txt} $4000 to 4999 {c |}{res}       114          0          0          0 {txt}{c |}{res}       114 
{txt} $5000 to 5999 {c |}{res}       145          0          0          0 {txt}{c |}{res}       145 
{txt} $6000 to 6999 {c |}{res}       150          0          0          0 {txt}{c |}{res}       150 
{txt} $7000 to 7999 {c |}{res}       204          0          0          0 {txt}{c |}{res}       204 
{txt} $8000 to 9999 {c |}{res}       375          0          0          0 {txt}{c |}{res}       375 
{txt}$10000 - 14999 {c |}{res}     1,247          0          0          0 {txt}{c |}{res}     1,247 
{txt}$15000 - 19999 {c |}{res}         0        972          0          0 {txt}{c |}{res}       972 
{txt}$20000 - 24999 {c |}{res}         0      1,362          0          0 {txt}{c |}{res}     1,362 
{txt}$25000 or more {c |}{res}         0          0     13,769          0 {txt}{c |}{res}    13,769 
{txt}       refused {c |}{res}         0          0          0        190 {txt}{c |}{res}       190 
{txt}{hline 15}{c +}{hline 44}{c +}{hline 10}
         Total {c |}{res}     2,910      2,334     13,769        190 {txt}{c |}{res}    19,203 
{txt}
{com}. 
. codebook age

{txt}{hline}
{res}age{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:AGE_3}, but {res:71} nonmissing values are not labeled

{col 18}Range: [{res}18{txt},{res}89{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}72{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}162{txt}/{res}21,648

{txt}{ralign 23: Examples:}{col 25}{res}32{col 31}{txt}
{ralign 23: }{col 25}{res}44{col 31}{txt}
{ralign 23: }{col 25}{res}54{col 31}{txt}
{ralign 23: }{col 25}{res}66{col 31}{txt}

{com}. codebook degree

{txt}{hline}
{res}degree{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:DEGREE_3}

{col 18}Range: [{res}0{txt},{res}4{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}5{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}3{col 50}{txt}Missing .*: {res}19{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     2,584{col 32}       0{col 42}{txt}lt high school
{col 20}{res}    10,720{col 32}       1{col 42}{txt}high school
{col 20}{res}     1,721{col 32}       2{col 42}{txt}junior college
{col 20}{res}     4,190{col 32}       3{col 42}{txt}bachelor
{col 20}{res}     2,414{col 32}       4{col 42}{txt}graduate
{col 20}{res}         2{col 32}      .a{col 42}
{col 20}         1{col 32}      .d{col 42}
{col 20}        16{col 32}      .n{col 42}
{txt}
{com}. codebook race

{txt}{hline}
{res}race{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:LABJG}

{col 18}Range: [{res}1{txt},{res}3{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}3{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}1,823{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}    15,043{col 32}       1{col 42}{txt}white
{col 20}{res}     2,989{col 32}       2{col 42}{txt}black
{col 20}{res}     1,793{col 32}       3{col 42}{txt}other
{col 20}{res}     1,823{col 32}      .y{col 42}
{txt}
{com}. codebook sex

{txt}{hline}
{res}sex{right:(unlabeled)}
{txt}{hline}

{col 19}Type: Numeric ({res}byte{txt})
{ralign 22:Label}: {res:SEX_3}

{col 18}Range: [{res}1{txt},{res}2{txt}]{col 55}Units: {res}1
{col 10}{txt}Unique values: {res}2{col 51}{txt}Missing .: {res}0{txt}/{res}21,648
{col 8}{txt}Unique mv codes: {res}1{col 50}{txt}Missing .*: {res}10{txt}/{res}21,648

{txt}{col 13}Tabulation: Freq.   Numeric  Label
{col 20}{res}     9,481{col 32}       1{col 42}{txt}male
{col 20}{res}    12,157{col 32}       2{col 42}{txt}female
{col 20}{res}        10{col 32}      .n{col 42}
{txt}
{com}. 
. keep panel_id panel monthintv dayintv year stata_intvdate rec_partyid polviews rec_natarms rec_natcrimy rec_natenvir rec_natfare rec_natrace rec_natsci rec_letin1a rec_income race sex degree age
{txt}
{com}. 
. /****Save data in .dta format for use in estimating comparison models***/
. 
. save "../GSS_2006_2020RecodedAppendedPanels.dta",replace
{txt}{p 0 4 2}
file {bf}
../GSS_2006_2020RecodedAppendedPanels.dta{rm}
saved
{p_end}

{com}. 
. /****Export dataset as excel file for use in Fortran code to estimate our models***/
. 
. export excel using "GSS_combined_panels_subset.xls", firstrow(variables) nolabel replace missing("-999")
{res}{txt}file {bf:GSS_combined_panels_subset.xls} saved

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Dropbox\Alecia\Stability of Political Attitudes\Replication Prep\GSS\data\recode\log_recode.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}10 Dec 2025, 19:20:37
{txt}{.-}
{smcl}
{txt}{sf}{ul off}